Why Your Freight Routing Guide Is Obsolete

The routing guides published by retailers to govern freight carrier selection for their inbound transportation have been in place for decades and are still widely used by many retailers today. The form of that guide has remained largely unchanged over this period – a static spreadsheet or database of state or lane combinations containing instructions for carrier selection that is published online or sent to vendors. The purchase order is sent from the retailer to vendor, the vendor then consults the retailer’s routing guide to determine which carrier is approved for that shipment (dictated by the retailer since they pay the freight bill). Additionally, there can be stiff penalties and/or chargebacks for vendor noncompliance to routing guides which often requires an expensive audit process for the retailer. Routing guides also present a significant operational challenge for vendors who have to manage dozens if not hundreds of unique routing requirements among their retail customers. The timing is right for technology-enabled solutions to replace static routing guides as our data exposes routing guides are neither adhered to nor as optimized as their authors believe. In fact, the freight routing guide is obsolete.

Increasing Retailer and Vendor Ecosystem Complexity

The rise of eCommerce has resulted in a proliferation of SKU counts for retailers, which in turn has resulted in supply chain complexity, including burgeoning vendor networks. Many of the leading retailers in the US have multiple thousands of vendors, many of which are domestic and require inbound freight coordination. Combine this complexity with the increasingly popular drop shipping trends and carrier innovations around minimum charges, discounts, weight breaks, dimensional pricing and most important, real time spot rate pricing, and it’s easy to understand how “paper” or static spreadsheets can quickly become obsolete and difficult to enforce.

Static Routing Guides Can’t Adapt to Dynamic Transportation Decisions

The above mentioned vendor proliferation and carrier innovations are creating problems for retailers using conventional transportation routing guides along two dimensions – 1) ensuring vendor compliance to the routing guide and 2) the routing guide’s inability to truly optimize carrier selection at the shipment level and in real time.

There are three important observations from our analysis of actual LTL shipment data, representing approximately 2M domestic LTL transactions over the past 12 months (vendor inbound or drop ship). All transactions represented retailer-paid freight shipments across carriers in their network (meaning they had negotiated rates with their carriers directly, not through a 3PL). We recognize this is a small sample, but observations discussed here have been consistent in the data, our experience and retailer surveys.

“yielded average compliance of 52%”

1. Routing guide compliance by vendors was surprisingly low in the sample, even for large retailers.
Comparing published routing guides to the carriers that were actually chosen for each shipment yielded average compliance of 52%, with a small variance in this percentage across retailers. We also observed that vendors are often either highly noncompliant or highly compliant, with those noncompliant vendors often defaulting to their preferred carrier for almost every shipment, despite the fact that the retailer may have 5-15 negotiated carrier relationships and a routing guide that reflects required usage across them. In particular, we observed the propensity of noncompliant vendors to default to national carriers (v. regional carriers) if they are listed as one of the retailer’s preferred carriers, regardless of which carrier the routing guide calls for on a particular shipment. While we do not have data to support the precise cause of this phenomenon, it could be due to a number of factors including brand strength, familiarity from parcel shipping, website features, better tracking and/or ease of use from the vendor’s point of view.

“10-20% freight cost reduction opportunity”

2. Routing guides do a poor job of optimizing on low cost carrier for each shipment.
In other words, the routing guide itself is suboptimal based on actual shipment characteristics. (i.e. minimum charge vs. discount %, weight break, mode). Even if there were 100% compliance to the routing guide by vendors, the result would be higher freight costs to the retailer than if carrier selection was optimized for lowest cost for each shipment among the retailer’s current carrier base. Now there are often reasons why the low cost carrier might not always be chosen for a particular shipment (which is described below) and in cases where this was known, we eliminated the bias from the data. In general, we observe cost to be the current primary driver for desired routing guide compliance, but our analysis consistently shows a 10-20% freight cost reduction opportunity had the low cost carrier been chosen for each individual shipment.

“there was an opportunity to reduce both cost and transit time”

3. Static routing guides are incapable of true shipment level optimization which goes beyond low cost carrier choice.
While we observed consistent patterns across retailers, in a particular retail case, 72% of the shipments were not optimized on low cost. Of these shipments, 67% of them would have also resulted in an equal or lower transit time. In other words, there was an opportunity to reduce both cost and transit time had the correct choice of carrier been made. Some, although a minority, of those low cost decisions would have had a negative consequence on delivery lead times. The point is that carrier decisioning should be based on many factors – cost, transit time, carrier performance, claims ratios – and all of it decisioned in real time by shipment characteristics, potentially even by customer. Imagine weighting carrier selection for a particular high value customer heavier for quicker delivery than for cost, and doing so in real time and executing the shipment automatically with no human choice or intervention. Or put another way, would a retailer spend 5% more on inbound or drop ship transportation if the reduced transit or increased reliability resulted in reduced customer churn and higher satisfaction was worth multiples more than the cost? Of course they would, assuming that there were tools in place to measure the impact of various carrier decision variables. That world is upon us.

Moving to a Dynamic, Automated Process for Carrier Selection and Shipment Execution

What is required to effectively manage the complexity of multiple carrier relationships, growing vendor networks, current and reliable pricing from carriers and shipment level optimization? A platform that connects the retailer to the retailer’s carriers and vendors via real time technology is necessary. Each shipment is carrier decisioned based on the unique characteristics of that shipment and done so automatically without vendor choice. True carrier choice optimization is not just about low cost, it involves a real time calculation based on shipment cost, transit time, carrier performance, claims ratio and other factors the retailer may dictate. The shipment is then executed automatically (pick up request, BOL generation, label production) through the platform where all the data is captured digitally and centralized for visibility and analytics. The key enabler for such a platform is the connective tissue between parties so that each shipment can be evaluated and decisioned instantaneously. That connective tissue is the API (Application Programming Interface) and it is the new EDI. In a recent survey, 55% of supply chain executives were considering the switch from EDI to API technology, despite the significant past and ongoing investment in EDI. Recent advances in API adoption by LTL carriers now create a foundation for innovation in this ecosystem.

The Next Frontier: Predictive Big Data Analytics

Once the transportation process for the retailer’s inbound transportation becomes fully automated and digitally executed, the data captured enables advanced analytics and insight. A few areas we will explore in upcoming posts include algorithmic carrier decisioning, predictive delivery exceptions for shipment tracking and predictive inventory availability for all in transit shipments, all resulting in increased revenue due to reduced customer churn, faster time to shelf and reduced freight and inventory costs.

About the Author

Rob Taylor

Rob brings two decades of entrepreneurial and founding leadership experience from building numerous successful venture and IPO-funded startups. Most recently, Rob was the President of BlackLocus, a SaaS software company which was acquired by The Home Depot in late 2012. Prior to BlackLocus, Rob was the EVP & GM of TrueCar (Nasdaq: TRUE), where Rob built the consumer direct business from the ground up. TrueCar completed its IPO in mid-2014. Rob Taylor on LinkedIn